Read 450K '.idat' files and compute raw or normalized beta-values.
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a character vector containing the paths to the .idat files stripped from the '_Grn.idat' suffix with one entry for each sample (.idat files for green and red intensities have to be in the same folder).
List object containing raw signal intensities. Result of calling
If set to 'Blood', a set of prespecified reference values are used for normalization. This is recommended if you plan to use
read450K reads .idat files and returns a list object containing raw signal intensities.
dont_normalize450K returns an ExpressionSet containing beta-values without normalization.
normalize450K performs dye bias correction using the extension controls probes followed by normalization by local regression (Heiss and Brenner, 2015) and returns an ExpressionSet containing beta-values, too.
read450K a list containing the methylated, unmethylated and control signal intensities. For
normalize450K an ExpressionSet containing beta-values, rows corresponding to CpG sites (named) and columns to samples (in the same order as 'idat_files').
A benchmark comparing the performance of this method with other normalization approaches is provided in the vignette.
Jonathan A. Heiss
Heiss JA, Brenner H (2015). Between-array normalization for 450K data. Frontiers in Genetics, doi:10.3389/fgene.2015.00092
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## Not run: library(minfiData) ## this package includes some .idat files library(data.table) path <- system.file("extdata",package="minfiData") samples = fread(file.path(path, 'SampleSheet.csv'),integer64='character') samples[,file:=file.path(path,Sentrix_ID,paste0(Sentrix_ID,'_',Sentrix_Position))] ## samples$file is a character vector containing the location of the ## .idat files, but without the suffixes "_Red.idat" or "_Grn.idat" raw = read450K(samples$file) none = dont_normalize450K(raw) ## no normalization norm = normalize450K(raw) ## End(Not run)
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